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改进的面向麻花钻刃形节能优化Dijkstra算法 被引量:2

Improvement of Dijkstra algorithm aiming at energy conservation optimization design of geometrical shape of twist drills
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摘要 将Dijkstra算法引入复杂刀具结构节能优化设计,提出了基于Dijkstra算法的麻花钻主刃曲线节能优化设计的方法.针对应用Dijkstra算法求解麻花钻最小钻削功率主刃曲线时存在计算精度不高、效率低、难以保证刃形曲线的光滑性和可刃磨性等问题,利用主刃曲线在半径方向不会发生回头式弯折的特点,提出将前刀面螺旋面离散网络进行径向分段与逐步缩小周向搜索范围来加密网格相结合的方式改进Dijkstra算法的求解过程,以降低其时间复杂度、提高计算效率和计算精度.计算结果表明:改进后的Dijkstra算法既可以使计算效率提高千倍以上,又可以很好地保证主刃曲线及其切削角度分布曲线的光滑性,提高优化主刃的可刃磨性. Dijkstra algorithm was introduced to the energy conservation optimization design of the structure of complicated cutting tools.The designing procedure of the geometrical shape and dimensions of the cutting edge of twist drills based on Dijkstra algorithm was proposed.The problems taken into consideration that the calculation efficiency is low,the calculated results are not sufficiently precise,and the smoothness and the machinability of the cutting edge curve cannot be guaranteed when the Dijkstra algorithm is used to determine the main cutting edge curve with minimal drilling power,a combination of two methods,dividing the discretized grids on the rake face into several parts along the radius direction,and gradually decreasing the searching scope to refine mesh along the circumference,was proposed to improve Dijkstra algorithm to reduce its time complexity and improve its calculation efficiency,since the main cutting edge is a curve with no inflexion along the radius direction.Calculation shows that the improved Dijkstra algorithm leads to an increase of calculation efficiency by over1 000 times,and it successfully results in smoothness of both the cutting edge curve and the distribution curves of cutting angles so that the machinability of the main cutting edge curve is guaranteed.
作者 熊良山
出处 《华中科技大学学报(自然科学版)》 EI CAS CSCD 北大核心 2015年第1期1-6,共6页 Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金 国家自然科学基金资助项目(51075165)
关键词 麻花钻 刃形 节能 优化设计 DIJKSTRA算法 复杂度 twist drill geometrical shape energy conservation optimization design Dijkstra algorithm complexity
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